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Hadoop Python Jobs in Portland, OR (NOW HIRING)

Smarsh

Linux DevOps Engineer

Portland, OR · On-site

... Python preferred) Experience working with relational databases (MS SQL and MySQL preferred) Strong troubleshooting skills Experience using Agile/Scrum methodologies Experience with Solr or Hadoop a ...

Nike

Lead Software Engineer

Beaverton, OR · On-site

Python for data processing and workflow orchestration * Informatica for building complex ETL ... Hive on Hadoop ecosystems * Unix programming * Data Architecture to support petabyte scale ...

Smarsh

DevOps Team Lead

Portland, OR · On-site

$56 - $76.50/hr

... Python preferred) • Experience working with relational databases (MS SQL and MySQL preferred) • ... Openstack, AWS, Hadoop a bonus • Experience using Agile/Scrum methodologies Additional ...

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All JobsHadoop Python JobsHadoop Python Jobs in Portland, OR

Hadoop Python information

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$10

$63

$77

How much do hadoop python jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for hadoop python in Portland, OR is $63.52, according to ZipRecruiter salary data. Most workers in this role earn between $60.43 and $69.33 per hour, depending on experience, location, and employer.

What is a Hadoop Python developer?

A Hadoop Python developer is a software professional who specializes in using Python programming language to develop, implement, and maintain applications that process and analyze large datasets within the Hadoop ecosystem. They leverage Python libraries like PySpark to write scalable data processing scripts, interact with Hadoop components such as HDFS, and optimize big data workflows. These developers play a critical role in building data pipelines, performing data transformation, and supporting analytics projects in organizations that handle vast amounts of data.

What are the key skills and qualifications needed to thrive as a Hadoop Python developer?

To thrive as a Hadoop Python Developer, you need a strong understanding of distributed computing, Hadoop ecosystem components (like HDFS, MapReduce, Hive, or Pig), and advanced Python programming skills, often supported by a degree in computer science or related field. Familiarity with tools such as Apache Spark, Sqoop, and workflow schedulers (like Oozie or Airflow), along with experience in handling big data platforms, is typically required. Problem-solving abilities, attention to detail, and effective communication help developers collaborate with teams and translate business requirements into scalable data solutions. These skills and qualifications are essential for efficiently processing and analyzing large datasets, ensuring data reliability, and driving business insights.

How do Hadoop Python developers typically collaborate with data engineers and analysts on large-scale data projects?

Hadoop Python developers frequently work alongside data engineers and analysts to design, implement, and optimize data pipelines for handling vast datasets. They are responsible for writing Python scripts that interface with Hadoop components, ensuring data is processed efficiently and meets project requirements. Regular communication with data engineers helps align on infrastructure and architectural decisions, while close collaboration with analysts ensures data outputs are accurate and actionable. Agile methodologies and daily stand-ups are common, fostering teamwork and quick problem-solving.

What is the difference between Hadoop Python vs Hadoop Java Developer?

AspectHadoop PythonHadoop Java Developer
Required CredentialsPython programming skills, Hadoop certificationsJava programming skills, Hadoop certifications
Work EnvironmentData analysis, scripting, data pipeline developmentCore development, system integration, big data application coding
Industry UsageData science, analytics, machine learning projectsData infrastructure, platform development, system optimization

Hadoop Python and Hadoop Java Developer roles both involve working with Hadoop ecosystems, but Python focuses more on data analysis and scripting, while Java is geared towards core development and system integration. The choice depends on your programming expertise and career goals within big data environments.

What are jobs in Hadoop Python?

Jobs in Hadoop Python typically involve developing and maintaining data processing tasks using Python scripts within the Hadoop ecosystem. These roles often require knowledge of Hadoop frameworks like MapReduce or Spark, along with Python programming skills, to handle large-scale data analysis and processing tasks. They may also involve working with distributed systems and data pipelines in a big data environment.

What are popular job titles related to Hadoop Python jobs in Portland, OR?

For Hadoop Python jobs in Portland, OR, the most frequently searched job titles are:

What job categories do people searching Hadoop Python jobs in Portland, OR look for?

The top searched job categories for Hadoop Python jobs in Portland, OR are:

Hadoop Python jobs near you
Infographic showing various Hadoop Python job openings in Portland, OR as of July 2026, with employment types broken down into 88% Full Time, 4% Part Time, and 8% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $132,113 per year, or $63.5 per hour.

Data Engineer

Rootshell Enterprise Technologies, Inc.

Portland, OR • On-site

$120K - $144K/yr

Full-time

Re-posted 18 days ago

Job description

Hi All,
Hope you are doing great!
This is Himabindu from Rootshell Inc. We have an immediate need for below mention requirement, if you feel that you are a perfect match to this requirement, please forward your most updated resume along with the best time and number to carry out further discussions.
Looking forward to hear from you...
Role: Big Data Engineer
Location: Portland OR
Position:Long term
Role Expectations:
Strong experience in Scala or Python.
Experience building domain-driven microservices.
Experience with data modeling in different data stores and the Hadoop ecosystem. -
Experience working with data stores such as Snowflake, DynamoDB, etc. -
Experience working with Big Data frameworks such as Spark, Hive, Nifi, Spark-streaming, Kinesis, Kafka, etc. -
Experience with performance and scalability tuning. -
Experience working with schema evolution, serialization, and validation with file formats such as JSON, Parquet, Avro, etc.
Experience working in the AWS environment, specifically S3 and EMR. - Experience working with Airflow.
Familiarity with practices such as CI/CD and Automated testing.
Agile/Scrum Application development experience.
An interest in artificial intelligence and machine learning.

Apply